Work-life balance as predictors of job satisfaction in the tertiary educational sector

Abstract

This paper examines work-life balance as a predictor of job satisfaction in the tertiary education sector. The structural equation model was used to quantitatively analyse cross-sectional data gathered from 476 employees of 8 tertiary institutions operating in the Greater Accra region of Ghana. The study concludes that workplace support has a positive effect on personal life interference with work, and work interference with personal life. Work interference with personal life and personal life interference with work had a negative relationship with satisfaction with work life. The study recommends that personal life interference with work and work interference with the personal life of workers should be a priority of tertiary institutions, as it will help improve workplace support.

Keywords:

• improved effectiveness at work
• personal life interference
• structural equation model
• work interference with personal life
• workplace supports

PUBLIC INTEREST STATEMENT

This paper assesses the relationship between the work-life balance of workers in tertiary institutions in Ghana and how that affects their level of job satisfaction using primary data and the structural equation model. The results show that for work-life balance to positively influence job satisfaction of individuals it is important to increase workplace support (WPS) and improve the effectiveness in which work is done.

1. Introduction

Recently, considerable attention has been given to issues of “Work-life balance” (WLB) with companies across the world adopting and testing new policies to help their employees better manage time spent, between work and personal activities. The work-life balance has grown into more than just an appealing concept. According to Guest (2002), and Kerdpitak and Jermsittiparsert (2020), work-life balance is the ability of a worker to manage both paid work and social life adequately. One’s ability to manage both domains effectively dwells on the approach employed by both employers and employees (Wilkinson et al., 2018). Previous studies contend that, when management provides benefits to employees, employees incline to feel obligated to the organisation and make more considerable efforts, to safeguard its well-being and achieve its goal (Vayre, 2019). However, an increasing number of institutions are relying on their employees to lead a more balanced lifestyle, since employees are ultimately more productive and motivated when happy. Aside from this, in today’s fast-paced society, human resource professionals seek options to positively impact the bottom line of their companies, improve employee morale, retain employees with valuable company knowledge, and keep pace with workplace trends. That said, if an institution either consciously or unconsciously, destroys an employee’s private life with too much overtime or an unnatural amount of pressure, the result then is dissatisfaction and stress, which can lead to health problems, decreased productivity, and alienation from the company. Employees’ attitudes and behaviours are subject to their motivation, which directly affect the organizational competitive advantage (Aryee et al., 2013).

Determining the link between work-life balance and commitment, Beauregard and Henry (2009) claim that commitment to work hangs largely on the degree to which employees can balance work and non-work activities, whilst being content with the work they accomplish and the services they render. With this, the ability of any institution to compete well in the global market, with high-quality standards requires granting employees flexible work arrangements for employees to be able to display a positive work attitude. In ensuring competitive advantage, most institutions have put together policies such as study leave, casual leave, job sharing, family support services and many more, to ensure effective work-life balance.

In Ghana, Asiedu-Appiah et al. (2016) contend that paid work and non-work activities are two significant domains, since longer work hours at the office lower employee’s home presence and cause them to frequently miss family and social activities. Thus, little is known about work‐life balance among tertiary educational workers and their level of satisfaction with the jobs that they do. Several studies have identified workplace support, work interference with personal life, personal life interference with work, and effectiveness at work to be related to satisfaction with work-life balance (Chung & Van der Lippe, 2020; Peng et al., 2021). That notwithstanding, workplace support has been identified to improve efficiency and effectiveness, by reducing inefficiencies and ineffectiveness linked to unresolved stress, conflict, and other issues affecting employees’ well-being and performance at work. This has a direct effect on job satisfaction and performance. When the role constraints from the professional and personal life domains are conflicting in some way, it is called an inter-role conflict (Boamah et al., 2022). Work interference with family is one example. Work-related activities that interfere with family responsibilities are referred to as WIPL (Shabir et al., 2021). Work-life interference occurs, for instance, when a task from the office is completed at home on the weekend. Like how duties from one’s personal life might affect how well one performs at work; this phenomenon is known as personal life interference with work. For instance, a parent who works can get preoccupied with the presence of a sick child at home. Work-home interference typically falls into one of three categories.

Aside from these studies, limited studies have been conducted in Ghana. The question this study seeks to ask is; Do work-life balance policies affect employee job satisfaction? It is in the quest to find answers to such questions that this paper examines work-life balance as a predictor of employee job performance in the educational sector. The general objective of this study is to examine the effect of work-life balance on employee performance. More specifically, the paper seeks to examine the effect of workplace supports (WPS) and work interference with personal life (WIPL), workplace supports and personal life interference with work (PLIW), work interference with personal life and satisfaction with work-life balance (SWLB) on satisfaction with work life and improved effectiveness at work (IEW). In addition to this, the following hypothesis is examined:

• H01 = There is no significant relationship between Workplace Support and Work Interference with Personal Life

• H02 = There is no significant relationship between Workplace Support and Personal Life Interference with Work

• H03 = There is no significant relationship between Work Interference with Personal Life and Satisfaction with Work-Life Balance

• H04 = There is no significant relationship between Personal Life Interference with Work and Satisfaction with Work-Life Balance

• H05 = There is no significant relationship between Satisfaction with Work-Life Balance and Improved Effectiveness at Work

2. Literature review

2.1. Theoretical framework: border theory

The argument in the empirical literature shows that no single theoretical literature has been universally accepted when it comes to the issues of work-life balance (Wilkinson et al., 2018). Despite this, the interaction between work and non-work or family life has been largely studied using five basic models (Ninaus et al., 2021), though there are more theories on work-life balance. Generally, the academic literature has presented theories such as segmentation, enrichment/enhancement, facilitation, spillover, social identity, compensation, congruence, conflict, human capital, instrumental, resource drain, conservation of resources, ecology, border, integration and ladder theories (Bakker et al., 2009; Greenhaus & Powell, 2006; Krouse & Afifi, 2007; Zedeck & Mosier, 1990).

Segmentation theory is the earliest theory developed on the work-life balance. The theory reflects work and family as diverse entities and experiences, hence, one will not influence or affect the experiences of the other (Kelliher et al., 2019; Young & Kleiner, 1992). This implies that there is no direct impact of work on the family unit, nor does the family unit have any influence on work life. The enrichment proposed by Seiber (1974) and further expanded by researchers such as Chan et al. (2016) and Haar (2013) is that engagement in multiple roles, or role accumulation provides access to various resources that can be utilised by individuals across various role performances. Thus, the enrichment theory focuses on the extent to which experiences in one role improve the quality of life in the other. An offshoot of the enrichment theory, the facilitation theory argues from the extent to which individuals’ participation in one life domain (e.g., work) may bring resources, and pleasurable and enriching experiences to another role (Barnett & Hyde, 2001; Nicklin & McNall, 2013), or is made easier by the skills, experiences and opportunities gained by their participation in another domain (Frone, 2003; Sanders & Stappers, 2008). These theories have been criticized for being mostly descriptive, failing to emphasise causes and consequences, and failing to provide a framework for analysing the work-life balance (Guest, 2002). Clark (2000) proposed Border Theory (BT) as a response to this argument. BT opens a rich vein of analysis focused on the nature of work and family domains, on the borders between these two domains, adding these borders’ permeability and the ease with which the borders can be managed or moved” (Clark, 2000). According to Guest (2002) and Peng et al. (2021) individuals can achieve work-family balance (WFB) by managing and negotiating the work and family spheres and the borders between them to attain balance. Work and family, according to BT, are two distinct yet intertwined settings in which people have associated various rules, feelings, values, cognitive patterns, and behaviours (Wöhrmann et al., 2021). Individuals are viewed as border-crossers who manage and negotiate the work and family spheres, as well as the borders that separate them, to achieve WFB. According to Clark (2000), balance is defined as “satisfaction and good functioning at work and home with a minimum of role conflict.” WFB is viewed as a state that leads to a variety of satisfaction that is valued by the individual and his/her stakeholders, allowing for the evaluation of one’s actions within a situational context (Chung & Van der Lippe, 2020; Reiter, 2007). Also, Raza et al. (2018) studied the moderating effect of work-family conflict between the relationship of mindfulness and work-family balance in public and private hospitals in Lahore, Pakistan. Their finding shows that work-family balance has a positive influence on job satisfaction and trait mindfulness has a positive impact on work-family balance. The finding of Mundia and Wu (2019) from a random sample of 860 Brunei public and private sector shows that male employees were more satisfied than their female peers. In addition, workers in the Brunei-Muara district were also more satisfied than their counterparts in other districts.

3. Methodology

3.1. The study area

The Greater Accra Region was chosen for the study because it is the political and administrative capital city of Ghana, and is busy always with human activities. Also, the Greater Accra Region has the most tertiary educational institutions and experiences a lot of Tertiary educational institutions springing up each passing month and year. The rationale for selecting this study area was that there is a high tendency for employees to experience WLB due to the student numbers in the various institutions. Implying that the workload of employees is likely to be more relative to their counterparts in other areas of the country.

3.2. Study design

The study adopted a descriptive cross-sectional survey design to develop an in-depth understanding of the topic. The descriptive research design was employed to explore the relationship between work-life balance and job satisfaction in the tertiary education sector. Thus, the design employed helped in studying respondents in their natural setting (work environment). Further, the descriptive research design helped in describing the behaviour of respondents in the research process whilst examining their work-life balance concerning job satisfaction.

3.3. Study population and sampling

The population for the study was made up of universities operating in the Greater Accra region of Ghana. The population of the study was 24 universities, made up of five public universities and 19 privately owned universities. Out of this number, eight universities were selected. The study purposively selected four public universities, that is, the University of Ghana (UG), the University of Professional Studies (UPSA), Accra Tech University, and Ghana Communication Technology University. The choice of four out of five public universities was because, at the time of the study, the fifth university was being considered by the parliament of Ghana for full public university status. The four private universities which were purposively selected are Accra Institute of Technology (AIT), Christian University College, Valley View University college, and Wisconsin University College. The rationale for the choice of public universities is that they are well structured, have been operating for a long, and have larger student numbers. In the case of the private universities students’ numbers and the availability of permanent teaching, staff were used as the basis for selection. Further, the choice of private and public universities was to cater for diversity and heterogeneity (Asravor, 2021). On average 53 employees were selected from each of the eight universities. To ensure that the sample size was not reduced by incomplete responses, does not reduce the sample size, an oversampling was done in this study. Thus, the sample data collected in this study was 480, out of which four were dropped due to incompletion of the questionnaire. The sample used for this study was 476 respondents. The sample size used for this study included Professors, Senior Lecturers, Lecturers, accountants, auditors, clerks, secretaries, receptionists, technicians, and security officers.

3.4. Data collection instruments/techniques

The study utilised primary data collected from respondents from the universities operating in the Greater Accra region of Ghana. Primary data were obtained by administering online questionnaires, which helped the researchers to elicit insightful data to support this work. Online questionnaires were solely used due to the Covid 19 pandemic. The questionnaires helped establish the relationship between work-life balance and job satisfaction. Questionnaires administered online by the researchers to employees in their respective institutions were monitored every two days to check on the rate of response. Researchers gave themselves an ample time of three weeks to complete the process.

3.5. Data analysis

The data obtained from the questionnaires were cleaned, coded, and analysed using the Statistical Product and Service Solutions (SPSS) software version 20. The structural equation model was performed using the AMOS software.

4. Results and discussion

4.1. Socio-demographic characteristics

Table 1 presents the descriptive statistics of respondents. In all 57.14% of the respondents were males and the majority were between the ages of 25 and 35 (61.97%). The most represented educational level was Master’s (33.40%) and in terms of years of working, 42.02% of the respondents have been working for between 5 and 10 years.

Table 1. Demographic profile of the respondents

		%
Gender	Male	272	57.14
	Female	204	42.86
Age	25–35	295	61.97
	36–45	123	25.84
	46–55	58	12.19
Educational Level	Secondary	51	10.71
	HND	78	16.39
	1^st Degree	138	29
	Masters	159	33.4
	Doctoral Degree	50	10.5
Year of Working	0–5 Years	241	50.63
	5–10 Years	200	42.02
	10–15 Years	12	2.52
	More than 15 Years	23	4.83

4.2. Reliability and validity

Table 2 shows that Cronbach’s alpha coefficient (α) which ranges from 0.731 to 0.801 were above the recommended score of 0.70 (Robinson et al., 1991). This implies that Cronbach’s alpha coefficient falls within the acceptable range, hence, is reliable, which means that all reliability measures are robust.

Table 2. Factor loadings, composite reliability, and AVE for construct

		Skewness	Kurtosis	Factor Loading(> 0.5)	CR (> 0.60)	α (> 0.70)	AVE (> 0.50)
WPS
	X1	−0.0084	−2.0084	0.847	0.80107676	0.8012895	0.5479972
	X3	−5.3019	−8.7929	0.590
	X4	−0.1384	−1.3170	0.604
	X5	0.3336	−1.5323	0.612
WIPL
	X8	−0.2884	−1.1177	0.791	0.7712145	0.7313173	0.5382495
	X9	−9.0429	−0.7745	0.536
	X10	−1.1178	0.1181	0.681
	X11	−4.8972	−1.5046	0.892
PLIW
	X13	−5.0686	−1.1930	0.591	0.7756141	0.7625261	0.5173491
	X14	−0.3063	−1.4448	0.547
	X15	−5.7839	−1.2106	0.776
	X16	−4.8748	−0.7344	0.767
SWLB
	X18	−5.7894	−0.9771	0.724	0.8130486	0.7997156	0.54092
	X19	0.508	−0.876	0.508
	X20	0.858	−0.536	0.858
	X21	0.858	−0.184	0.858
IEW
	X22	0.533	−0.975	0.533	0.7887381	0.7607171	0.5697077
	X7	−5.1533	−1.0986	0.742
	X17	0.0879	−1.2711	0.900
	X12	0.1409	1.2322	0.900

Also, the convergent validity indicates that the CR (0.771–0.813) and the AVE (0.517–0.569) were above the recommended scores of 0.6 and 0.5 respectively (Bagozzi & Yi, 2012; Fornell & Larcker, 1981), hence, were within the acceptable ranges (Table 2). The factor loadings for each of the variables were equally greater than 0.4 as recommended by Hair et al. (2010), hence, the data was deemed acceptable to be used for the structural educational model.

Acceptable discriminant validity is observed when the variances extracted from the constructs are greater than the squared correlations among variables (Saroia & Gao, 2018). As observed from Table 3, the elements in the matrix diagonals (square roots of the AVEs) are larger than the off-diagonal elements indicating that the constructs were analytically different and good. Thus, the scale used in this study was discriminately valid. of our scales.

Table 3. Discriminant validity (inter-correlations)

	WPS	WIPL	PLIW	SWLB	IEW
WPS	0.740
WIPL	0.636	0.696	0.719
PLIW	0.530	0.402	0.668
SWLB	0.122	0.359	0.404	0.750

4.3. Structural model and hypotheses testing

To address the objectives and test the hypothesis of the study, the structural equation model was employed. The structural model fit was employed to examine the hypothesized relationships between WPS, WIPL, PLIW, SWLB and IEW. To check and control for the effect of moderation, gender, age, educational level, and years of work were added to the correlation matrix along with the study variables (WPS, WIPL, PLIW, SWLB and IEW).

All the moderating variables indicated a weak correlation and were found not to be significantly correlated with the study variables, hence were not included in the final structural model (Figure 1). The standardized path coefficients of the structural model estimated by Rstudio was used to assess the magnitude and direction of relationships and test the study hypotheses (Table 4).

Figure 1. Path analysis.

Table 4. Hypotheses testing results

Hypothesis	Path	β	t-value	Results
H1	WPS->WIPL	0.310	6.217***	Support
H2	WPS->PLIW	0.180	4.676***	Support
H3	WIPL->SWLB	−0.700	−3.689***	Support
H4	PLIW->SWLB	−0.490	3.479***	Support
H5	SWLB->IEW	0.560	4.899***	Support

1st and 2nd variable on the path represents independent and dependent variables respectively; *,**, and *** indicated significant at 10%, 5% and 1% respectively

Hypothesis two (H2) shows the relationship between WPS and PLIW. The finding shows that WPS had a positive relationship with PLIW as indicated by the structural path coefficient (β = −0.18, t = 4.676). The findings of the study corroborate with previous research evidence (Agha et al., 2017). This means that if the WPS is increased, there will be a tendency for the PLIW to increase, and vice versa. Therefore, it is possible that when a person is experiencing high levels of engagement and support at work, it may positively affect their attitudes. The finding of hypothesis one (H1) shows that WPS had a positive relationship with WIPL as indicated by the structural path coefficient (β = 0.31 t = 6.217). This finding corroborates Forsyth and Polzer-Debruyne (2007) and suggests that when an employee perceives that his/her employer is supportive, the person can integrate family and work-related issues, which results in a higher level of job satisfaction. Thus, support from work colleagues and managers serves as a serious motivator towards ensuring effective work is integrated into personal life which finally culminates into job satisfaction.

Both WIPL and PLIW had a negative relationship with SWL as depicted by the structural path coefficient (β = −0.70, t = −3.689) and (β = −0.490, t = 3.479), respectively which answers hypothesis three (H3) and hypothesis four (H4). Thus, work-life balance is significantly related to job satisfaction, and workers who have a high Work-Life Balance also have high job satisfaction. SWL also had a positive relationship with IEW as indicated by the structural path coefficient (β = −0.560, t = 4.899), which answers the fifth hypothesis (H5). Thus, the dimension of satisfaction is influenced by the efforts to improve performance or productivity (IEW). All the study hypotheses were accepted indicating that they support the hypothesis stated.

Table 5 present the fit indices and the validation analysis of the hypothesised model, and the results showed that each path coefficient was statistically significant. The model shows that all values are acceptable signifying a high model fit. Thus, the model fit shows a good model fit index.

Table 5. Fit Indices

Fit indices	Recommended values	Value	Remarks
Chi-square (X^2/df)	< 5 preferably <3	4.22	Good fit
Goodness of fit index(GFI)	> 0.90	0.91	Good fit
Adjusted Goodness of fit(AGFI)	> 0.80	0.87	Good fit
Comparative fit index(CFI)	> 0.90	0.91	Good fit
Root mean square error of approximation(RMSEA)	> 0.08	0.28	Good fit
Root mean square residual(RMR)	< 0.05	0.006	Good fit
Non-normal fit index(NFI)	> 0.90	0.912	Good fit
PNFI	> 0.60	0.611	Good fit

5. Conclusions and recommendations

This study extends the concept of work-life balance to workers in the tertiary education sector of Ghana. Under the general objective of examining the effects of work-life balance on employee job satisfaction. The study used primary data collected from workers from both private and public tertiary institutions in Ghana. Employing both descriptive statistics and a structural equation model, the finding of the study shows that an increase in workplace support is directly associated with personal life interference with work and work interference with personal life which addressed hypothesis two. An inverse relationship is experienced with satisfaction with work-life balance when work interference with personal life (hypothesis three) and personal life interference (hypothesis four) with work is increased. Furthermore, satisfaction with work-life balance directly improves effectiveness at work (hypothesis five). Based on these findings, the study recommends that it is important that personal life interference with work and work interference with the personal life of workers should be a priority of tertiary institutions as it will help reduce workplace support. This will lead to a reduction in the cost incurred in the provision of workplace support as well as the productivity associated with this effort.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Afia Nyarko Boakye

Afia Nyarko Boakye is a Lecturer at the Department of Management and Human Resource of the Ghana Communication Technology University. Her research interests include Organisational Behaviour/ Management, Human Resource, and Leadership.

Richard Kofi Asravor

Richard Kofi Asravor is a Senior Lecturer and currently the head of Department of the Economics at the Ghana Communication Technology University. His interest is related to issues of Agricultural and Development Economics, Labour and Gender Economics, Inequality, and Poverty.

John Essuman

John Essuman is a Lecturer at the Department of Mathematics of the Ghana Communication Technology University. His interest is in Mathematical Modelling.